Hamad Eradah O, Savundranayagam Marie Y, Holmes Jeffrey D, Kinsella Elizabeth Anne, Johnson Andrew M
Department of Psychology, Faculty of Arts and Humanities, King Abdulaziz University, Jeddah, Saudi Arabia.
J Med Internet Res. 2016 Mar 8;18(3):e60. doi: 10.2196/jmir.5391.
Twitter's 140-character microblog posts are increasingly used to access information and facilitate discussions among health care professionals and between patients with chronic conditions and their caregivers. Recently, efforts have emerged to investigate the content of health care-related posts on Twitter. This marks a new area for researchers to investigate and apply content analysis (CA). In current infodemiology, infoveillance and digital disease detection research initiatives, quantitative and qualitative Twitter data are often combined, and there are no clear guidelines for researchers to follow when collecting and evaluating Twitter-driven content.
The aim of this study was to identify studies on health care and social media that used Twitter feeds as a primary data source and CA as an analysis technique. We evaluated the resulting 18 studies based on a narrative review of previous methodological studies and textbooks to determine the criteria and main features of quantitative and qualitative CA. We then used the key features of CA and mixed-methods research designs to propose the combined content-analysis (CCA) model as a solid research framework for designing, conducting, and evaluating investigations of Twitter-driven content.
We conducted a PubMed search to collect studies published between 2010 and 2014 that used CA to analyze health care-related tweets. The PubMed search and reference list checks of selected papers identified 21 papers. We excluded 3 papers and further analyzed 18.
Results suggest that the methods used in these studies were not purely quantitative or qualitative, and the mixed-methods design was not explicitly chosen for data collection and analysis. A solid research framework is needed for researchers who intend to analyze Twitter data through the use of CA.
We propose the CCA model as a useful framework that provides a straightforward approach to guide Twitter-driven studies and that adds rigor to health care social media investigations. We provide suggestions for the use of the CCA model in elder care-related contexts.
推特上140字符的微博帖子越来越多地被用于获取信息，并促进医疗保健专业人员之间以及慢性病患者与其护理人员之间的讨论。最近，人们开始努力调查推特上与医疗保健相关的帖子内容。这为研究人员开辟了一个新的调查和应用内容分析（CA）的领域。在当前的信息流行病学、信息监测和数字疾病检测研究计划中，推特数据的定量和定性数据经常被结合使用，并且在收集和评估推特驱动的内容时，没有明确的指导方针供研究人员遵循。
本研究的目的是识别将推特动态作为主要数据源并将内容分析作为分析技术的医疗保健和社交媒体研究。我们基于对先前方法学研究和教科书的叙述性综述，对由此产生的18项研究进行了评估，以确定定量和定性内容分析的标准和主要特征。然后，我们利用内容分析的关键特征和混合方法研究设计，提出了组合内容分析（CCA）模型，作为设计、开展和评估推特驱动内容调查的坚实研究框架。
我们进行了一次PubMed搜索，以收集2010年至2014年期间发表的使用内容分析来分析与医疗保健相关推文的研究。PubMed搜索和对所选论文的参考文献列表检查共识别出21篇论文。我们排除了3篇论文，并对18篇进行了进一步分析。
结果表明，这些研究中使用的方法并非纯粹的定量或定性方法，并且在数据收集和分析时并未明确选择混合方法设计。对于打算通过使用内容分析来分析推特数据的研究人员来说，需要一个坚实的研究框架。
我们提出组合内容分析模型作为一个有用的框架，它提供了一种直接的方法来指导推特驱动的研究，并为医疗保健社交媒体调查增添严谨性。我们为在老年护理相关背景下使用组合内容分析模型提供了建议。
